Abstract

Typical seismic data provide information about subsurface stratigraphy and structure. Formation characteristics, such as lithology and fluid content, can also be predicted from seismic data. Well-log data can verify seismically extracted formation characteristics. However, well drilling is relatively expensive and the success rate of commercially viable exploration wells, depending on the seismic data, is only about 10–30% (Johansen et al., 2005). Additional remote sensing methods for the detection of subsurface formation properties (e.g. resistivity) can be used to minimize the uncertainties associated with drilling. The recently developed SeaBed Logging (SLB) method shows a very promising potential for the detection of deeply buried highresistivity layers (Eidesmo et al., 2002). Resistivity contrasts in the subsurface strata make SBL a potential tool for the detection of high-resistivity hydrocarbon reservoirs or other high-resistivity lithologies, such as salt domes, volcanic rocks or igneous sills. The first fullscale SBL calibration survey was conducted offshore Angola in 2000 (Ellingsrud et al., 2002), opening a new frontier in hydrocarbon exploration. Subsequently, several surveys were performed over known hydrocarbon fields offshore Norway. SBL calibration surveys from Ormen Lange and Troll Western gas province have been presented by Røsten et al. (2003) and Johansen et al. (2005), respectively. In this article, we present SBL data acquired across the Modgunn arch, which is located in the Norwegian Sea. The SBL data interpretation aims at finding the resistivity distribution within the seismically interpreted subsurface strata. The Modgunn arch is characterized by strong seismic anomalies, which may partially correspond to high-resistivity anomalies. The SBL data of this area, in parts, show strata with high resistivity. SBL data analysis can predict the presence of the high-resistivity layers and rocks, but due to low resolution, it is difficult to determine the exact geometry of the resistivity structure from the SBL data alone. To establish the quantitative relationship between the seismic anomalies and the resistivity distribution within the strata, SBL and seismic data interpretation play complementary roles. The integrated approach of seismic and SBL data interpretation provides a realistic subsurface resistivity distribution with fewer uncertainties. An interpretation study, based on electric field magnitudes taken from the same data set, has been presented by Bhuiyan et al. (2005).

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